docs: Add explanation on how to use Hugging Face embeddings (#22118)

- **Description:** I've added a tab on embedding text with LangChain
using Hugging Face models to here:
https://python.langchain.com/v0.2/docs/how_to/embed_text/. HF was
mentioned in the running text, but not in the tabs, which I thought was
odd.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** No need, this is tiny :) 

Also, I had a ton of issues with the poetry docs/lint install, so I
haven't linted this. Apologies for that.

cc @Jofthomas 

- Tom Aarsen
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@ -75,6 +75,31 @@ Otherwise you can initialize without any params:
from langchain_cohere import CohereEmbeddings from langchain_cohere import CohereEmbeddings
embeddings_model = CohereEmbeddings() embeddings_model = CohereEmbeddings()
```
</TabItem>
<TabItem value="huggingface" label="Hugging Face">
To start we'll need to install the Hugging Face partner package:
```bash
pip install langchain-huggingface
```
You can then load any [Sentence Transformers model](https://huggingface.co/models?library=sentence-transformers) from the Hugging Face Hub.
```python
from langchain_huggingface import HuggingFaceEmbeddings
embeddings_model = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
```
You can also leave the `model_name` blank to use the default [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) model.
```python
from langchain_huggingface import HuggingFaceEmbeddings
embeddings_model = HuggingFaceEmbeddings()
``` ```
</TabItem> </TabItem>